Similarity detection between virtual patients and medical curriculum using R
| Authors | |
|---|---|
| Year of publication | 2018 |
| Type | Article in Proceedings |
| Conference | Studies in Health Technology and Informatics 255 |
| MU Faculty or unit | |
| Citation | |
| Web | http://ebooks.iospress.nl/volumearticle/50507 |
| Doi | http://dx.doi.org/10.3233/978-1-61499-921-8-222 |
| Keywords | OPTIMED; R programming language; akutne.cz; medical curriculum; text similarity; virtual patient |
| Description | This paper presents the domain of information sciences, applied informatics and biomedical engineering, proposing to develop methods for an automated detection of similarities between two particular virtual learning environments - virtual patients at Akutne.cz and the OPTIMED curriculum management system - in order to provide support to clinically oriented stages of medical and healthcare studies. For this purpose, the authors used large amounts of text-based data collected by the system for mapping medical curricula and through the system for virtual patient authoring and delivery. The proposed text-mining algorithm for an automated detection of links between content entities of these systems has been successfully implemented by the means of a web-based toolbox. |
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